Title :
The research on the GA-based neuro-predictive control strategy for electric discharge machining process
Author_Institution :
Ind. Eng. Inst., Zhejiang Univ. of Sci. & Technol., Hangzhou, China
Abstract :
In this paper, in accordance with the time-varying and non-linear character in electric discharge machining (EDM) process, a simple single-input single-output system is presented to simulate the EDM process. Based on this, a new type of direct optimizing neuro-predictive control system based on improved genetic algorithms for EDM process is designed. Finally, experimental results show that this system has good self-adaptability and high reliability, which results in the higher productivity.
Keywords :
discharges (electric); genetic algorithms; machining; neurocontrollers; nonlinear control systems; predictive control; time-varying systems; electric discharge machining process; genetic algorithm; neuropredictive control; nonlinear systems; time-varying systems; Adaptive control; Algorithm design and analysis; Design optimization; Electrical equipment industry; Genetic algorithms; Machining; Neural networks; Production; Productivity; Time varying systems;
Conference_Titel :
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN :
0-7803-8403-2
DOI :
10.1109/ICMLC.2004.1382346